Their methods are heavily based on hybrid planning, model-predictive-control, and trajectory optimization which have many parallels to popular ML methodologies [1].
Boston Dynamics problem is not "inaccessibility of robot hardware" or that "they have to adopt more ML methods"... There are more expensive machines in the world that are wildly profitable. Their problem is that it is very very hard to make a business case for humanoid or quadrupedal robots that is not better solved by more standard automation systems that (for example) don't have to be charged every 30 minutes or have to climb up and down the stairs.
Boston Dynamics problem is not "inaccessibility of robot hardware" or that "they have to adopt more ML methods"... There are more expensive machines in the world that are wildly profitable. Their problem is that it is very very hard to make a business case for humanoid or quadrupedal robots that is not better solved by more standard automation systems that (for example) don't have to be charged every 30 minutes or have to climb up and down the stairs.
[1] https://www.youtube.com/watch?v=EGABAx52GKI